The interoperability of exergy and Life Cycle Thinking in assessing manufacturing sustainability: A review of hybrid approaches

Abstract Today, the Life Cycle Assessment (LCA) is the most employed tool for assessing the sustainability of products and processes, both from an environmental, social and economic point of view. Exergy is defined by literature as the amount of useful work that can be derived from a real system when it is brought into equilibrium with its environment. In the literature, it is considered an outstanding concept that can be applied to enhance the effectiveness of ordinary evaluation models such as LCA. The literature proposes a variety of hybrid approaches that combine Exergetic Analysis (EA) and LCA with different combination frameworks. The aim of this paper is to describe the potential of each hybrid method and to characterize the degree of interoperability between EA and LCA that each of them can provide. Nevertheless, there are drawbacks that seem to be too challenging to overcome: a variety of inconsistencies in the interpretation of the results due to the difficulty of the inventory phase and the ambiguity in the choice of the correct alternative in the standard databases; the link with old techniques that refers to obsolete approaches in finding data that suit to the updated goals and scopes; the difficulty in conducting an assessment affected by the least possible uncertainty. Following a theoretical overview of the principles of each hybrid method that binds EA and LCA, the authors want to provide a review from a completely different point of view than the state-of-the-art literature, on how effectively EA and LCA can interact with each other in order to provide a more holistic view of the system/process to be assessed. The fascinating circumstance that emerges from the review is that any exergy approach would be more effective if joined (not replaced) to the standard LCA, because it turned out to be complementary. This theory has long been developed by many authors in their case studies as a confirmation of what Gutowski wrote years ago: no single alternative criteria or subsidiary model, independently of how well aggregated, may offer a suitable answer for all conditions. Specifically, through this review, the practitioners would be able to choose the best suited hybrid methodology, according to their aims, join the outcomes together and achieve a transdisciplinary knowledge of the behavior of the study case system, in order to design the best improvement strategies.